A translational framework mapping clinical challenges to technology solutions in upper limb neurorehabilitation

Background Stroke and spinal cord injury (SCI) are leading causes of long-term upper limb (UL) impairment, imposing significant disability and economic burden. Outpatient neurorehabilitation can be critical for restoring function, yet therapists face complex challenges within the clinical process. These challenges, particularly in areas of assessment, patient engagement, and resource management, must be navigated in clinical reasoning and decision-making. While rehabilitation technologies offer potential solutions, their integration into and routine use in practice is limited by, among other reasons, a disconnect between development and clinical needs. We sought to develop a translational framework that identifies clinical process challenges in outpatient UL neurorehabilitation for stroke and SCI and maps them to technology-based solutions, guiding clinically relevant innovation. Methods Using an interpretive description methodology, we conducted a qualitative study at three sites of a large rehabilitation hospital network. Data were collected from 10 therapists (9 occupational, 1 physical) through 33 direct clinical observations (24 hours and 45 minutes), post-observation debriefs, and semi-structured interviews. Constant comparative analysis synthesized findings into challenge domains and technology solutions, validated through member checking. Results Five core challenge domains were identified: Assessment & Progress Tracking ; Knowledge Transfer ; Patient Engagement ; Home Program Implementation ; and Information & Resource Constraints . These were mapped to four technology solution categories: Remote Monitoring & Analytics , Education & Decision Support , Assistive & Therapeutic Technologies , and Gamified Interventions . The framework illustrates how these solutions address specific challenges, such as using remote monitoring to track home exercise adherence or gamified platforms to enhance patient motivation. Conclusions This study demonstrates the potential of using egocentric video to inform clinical decision-making in neurorehabilitation, particularly for hand function. The strong preference for video over metrics suggests clinical decision support systems should prioritize interpretable, observation-based information aligned with clinical reasoning processes.Despite implementation challenges, therapists across technical familiarity levels expressed trust in the system and willingness to use it regularly. These findings indicate that egocentric video systems can bridge the clinic-home divide when designed to match interest-holder priorities.